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July 24, 2018

Six Reasons Why You Need A Data Partner

Artemis Health

Problems in the benefits arena can pop up without warning, and you don’t want your team scrambling for information or putting out fires instead of making solid decisions for your population. Having a data partner not only solves problems for your benefits teams before they arise, but it can also help you evaluate your existing benefits programs, find opportunities for value and make a case for new applications.

Here are six reasons why you need a great data partner.

#1: You're short on time.

A data partner saves time by bringing you answers to complex problems. And that's because your data reports can show you what’s happening right now in your population. Having a data partner like Artemis helps you gather all your data in one location and allows you to easily look across feeds.

Prescription drug spending is a good example. A reliable data analysis tool can help you look at specific drugs that are driving spending. When armed with this data, your benefits team can work with your PBM to adjust your formulary to favor less expensive, but equivalent drugs.

A great data partner can save you time by being able to analyze Rx data quickly and without the need for expensive professional services. And accurate data can help you tell stories, share insights and promptly make decisions.

#2: You don't know how your members are using their benefits.

A well-designed data tool helps you look past the surface numbers and get deeper into how members are using their benefits. For example, an Artemis customer wanted to better understand how their members were receiving dialysis treatment care.

Using the Artemis Platform, they noticed a trend of high costs claims because their members were using out-of-network services. With the help of data, the Artemis customer could audit their network coverage and provide better communication through their benefits carrier to help them create target messaging and make sure they are choosing lower cost, in-network dialysis services.

#3: You're flying blind.

A data partner can help open your eyes, find real insights, and help you make informed decisions based on numbers. When an employer asked Artemis to help them justify the cost of hiring a vendor to conduct a dependent audit on their behalf, Artemis loaded de-identified data on these dependents into the Artemis Platform (after the review was completed) to find out how much savings they could expect by removing these members from their health and prescription plans.

The findings showed that  discontinuing coverage for ineligible dependents could save their organization an average of $78,000 a year on costs.

Data can help you add, adjust or change your plan design by opening your eyes to the future returns of your strategy.

#4: You don't know if the expensive programs you're adding are doing any good.

You want to add benefits programs and coverage to attract and retain talented employees, but how do you know if they’re worthwhile? Let’s look at an example: fertility coverage.  A great data partner can help you measure the results of your fertility benefits and make sure they're delivering ROI.

As we’ve discussed in a previous blog post, if an employee thinks they can save money and increase the chances of a successful pregnancy, then they will implant more than one embryo at a time because IVF treatments bill per implantation. This raises the chance of twins or other multiples, which is more likely to require expensive NICU stays, repeated appointments and more.

A reliable data partner can make the case to cover IVF treatments because you can analyze benefits data around members with maternity episodes and correlate them to both prices and risk bins. You could argue that med and Rx claims for these members would be lower if you covered IVF treatments because it helps encourage employees to implant a single embryo and thereby reduce health risks and healthcare costs.

#5: Your benefits expenses are only going up.

You need to find wasted spending and eliminate it to keep up with the cost of employee benefits, and a data partner is a key. A data partner can help you make sure your expenses are justified, impactful and necessary. Our Artemis Actionable Overspending App is built on a series of proprietary data models and can help our customers understand where their spending is inefficient. Instead of cutting programs or pushing costs to members, we allow benefits teams to make their spending count without sacrificing great benefits.

For example, say you are trending on Avoidable ER visits. Avoidable ER visits happen when members are visiting the emergency department for injuries and illnesses that can treat at an urgent care center, onsite clinic or primary care office. And sometimes these ER visits are out-of-network care. And when members utilize out-of-network providers, both your costs and theirs rise astronomically.

And this is where having a data partner can have a significant impact. Employers can use the data to direct their healthcare provider to target messaging and help members understand the best avenue for care and redirect them to less expensive, more convenient options.

#6: You don't know how your population stacks up against the norm.

A great data partner can help you measure against benchmarks and find gaps in care. For example, our Benchmarks App  uses a large data set that allows employers to compare their population against regional or national data. Our data includes no government payers, and will enable employers to understand trends and what they should be worried about now. This data helps analysts identify outliers in their population and gives them a better sense for how they stack up against the average.

Additionally, Artemis customers can create “custom” benchmarks using any measure currently in the tool.

Data partners save you time, money and energy you need to provide great benefits for your populations. With the right data partner, you can expect a responsive, supportive, collaborative, and empowering relationship that helps you make data-driven decisions.  

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